Digging Deeper: Learning Multi-Level Concept Hierarchies
arXiv:2603.10084v1 Announce Type: new Abstract: Although concept-based models promise interpretability by explaining predictions with human-understandable concepts, they typically rely on exhaustive annotations and treat concepts as flat and independent. To circumvent this, recent work has introduced Hierarchical Concept Embedding Models...
Equivariant Asynchronous Diffusion: An Adaptive Denoising Schedule for Accelerated Molecular Conformation Generation
arXiv:2603.10093v1 Announce Type: new Abstract: Recent 3D molecular generation methods primarily use asynchronous auto-regressive or synchronous diffusion models. While auto-regressive models build molecules sequentially, they're limited by a short horizon and a discrepancy between training and inference. Conversely, synchronous diffusion...
Hardware Efficient Approximate Convolution with Tunable Error Tolerance for CNNs
arXiv:2603.10100v1 Announce Type: new Abstract: Modern CNNs' high computational demands hinder edge deployment, as traditional ``hard'' sparsity (skipping mathematical zeros) loses effectiveness in deep layers or with smooth activations like Tanh. We propose a ``soft sparsity'' paradigm using a hardware...
DT-BEHRT: Disease Trajectory-aware Transformer for Interpretable Patient Representation Learning
arXiv:2603.10180v1 Announce Type: new Abstract: The growing adoption of electronic health record (EHR) systems has provided unprecedented opportunities for predictive modeling to guide clinical decision making. Structured EHRs contain longitudinal observations of patients across hospital visits, where each visit is...
Improving TabPFN's Synthetic Data Generation by Integrating Causal Structure
arXiv:2603.10254v1 Announce Type: new Abstract: Synthetic tabular data generation addresses data scarcity and privacy constraints in a variety of domains. Tabular Prior-Data Fitted Network (TabPFN), a recent foundation model for tabular data, has been shown capable of generating high-quality synthetic...
Robust Post-Training for Generative Recommenders: Why Exponential Reward-Weighted SFT Outperforms RLHF
arXiv:2603.10279v1 Announce Type: new Abstract: Aligning generative recommender systems to user preferences via post-training is critical for closing the gap between next-item prediction and actual recommendation quality. Existing post-training methods are ill-suited for production-scale systems: RLHF methods reward hack due...
GSVD for Geometry-Grounded Dataset Comparison: An Alignment Angle Is All You Need
arXiv:2603.10283v1 Announce Type: new Abstract: Geometry-grounded learning asks models to respect structure in the problem domain rather than treating observations as arbitrary vectors. Motivated by this view, we revisit a classical but underused primitive for comparing datasets: linear relations between...
How to make the most of your masked language model for protein engineering
arXiv:2603.10302v1 Announce Type: new Abstract: A plethora of protein language models have been released in recent years. Yet comparatively little work has addressed how to best sample from them to optimize desired biological properties. We fill this gap by proposing...
Federated Active Learning Under Extreme Non-IID and Global Class Imbalance
arXiv:2603.10341v1 Announce Type: new Abstract: Federated active learning (FAL) seeks to reduce annotation cost under privacy constraints, yet its effectiveness degrades in realistic settings with severe global class imbalance and highly heterogeneous clients. We conduct a systematic study of query-model...
Optimal Expert-Attention Allocation in Mixture-of-Experts: A Scalable Law for Dynamic Model Design
arXiv:2603.10379v1 Announce Type: new Abstract: This paper presents a novel extension of neural scaling laws to Mixture-of-Experts (MoE) models, focusing on the optimal allocation of compute between expert and attention sub-layers. As MoE architectures have emerged as an efficient method...
Variance-Aware Adaptive Weighting for Diffusion Model Training
arXiv:2603.10391v1 Announce Type: new Abstract: Diffusion models have recently achieved remarkable success in generative modeling, yet their training dynamics across different noise levels remain highly imbalanced, which can lead to inefficient optimization and unstable learning behavior. In this work, we...
Trump administration urges Supreme Court to allow it to revoke protected status for Haitian nationals
The Trump administration on Wednesday asked the Supreme Court to pause a ruling by a federal judge in Washington, D.C., that barred the government from ending a program that allows […]The postTrump administration urges Supreme Court to allow it to...
The First Amendment’s application to public university students: an explainer
Free speech on university campuses is a perennially hot topic, perhaps most recently reflected in protests about the Israeli-Palestinian conflict at places like Ball State University, Harvard, and Columbia. This […]The postThe First Amendment’s application to public university students: an...
SCOTUStoday for Wednesday, March 11
You’ve likely heard of AI bots being used improperly by lawyers, but what about lawsuits over AI bots practicing law without a license? Reuters reported on one such case last […]The postSCOTUStoday for Wednesday, March 11appeared first onSCOTUSblog.
FCC chair blasts Amazon after it criticizes SpaceX megaconstellation
Will it really take "centuries" for SpaceX to deploy its megaconstellation?
What crackdown? Trump's EPA enforcement claims don't pass sniff test.
75% of the criminal cases closed last fiscal year originated before Trump took office.
AI ‘actor’ Tilly Norwood put out the worst song I’ve ever heard
This song is an AI actor's rallying cry to other AI actors, urging them to keep going despite the naysayers who doubt their humanity. Literally no one can relate to this.
Ford’s new AI assistant will help fleet owners know if seatbelts are being used
Ford Pro AI debuted at Work Truck Week in Indianapolis and is now available to all of its U.S.-based Pro telematics subscribers.
Zendesk acquires agentic customer service startup Forethought
Forethought was years ahead of its time and the 2018 winner of TechCrunch Battlefield.
Lovable says it added $100M in revenue last month alone, with just 146 employees
Swedish vibe-coding unicorn Lovable crossed $400 million in annual recurring revenue (ARR) in February.
Replit snags $9B valuation 6 months after hitting $3B
Replit raised a new $400 million round and said it hopes to have $1B in ARR by year's end.
WordPress debuts a private workspace that runs in your browser via a new service, my.WordPress.net
WordPress’s new browser-based service lets users create private sites without hosting or signing up, turning the platform into a personal workspace for writing, research, and AI tools.
Meta’s Moltbook deal points to a future built around AI agents
Meta’s Moltbook acquisition may look odd at first, but the deal could signal how Meta sees AI agents shaping future advertising and commerce on an agentic web.
Amazon expands a program that lets customers shop from other retailers’ sites
The changes allow more merchants to participate in Amazon's Shop Direct program, which sends Amazon customers to other retailers' websites.
Liberty of Conscience, Political Process Theory, and Founding-Era Free Exercise
Religious freedom claimants have achieved tremendous success before the Supreme Court in recent years. Yet free exercise jurisprudence has bounced between skepticism and embrace...The postLiberty of Conscience, Political Process Theory, and Founding-Era Free Exerciseappeared first onHarvard Law Review.
Sun Valley Orchards, LLCv. United States Department of Labor
In SEC v. Jarkesy, the Supreme Court failed to fully clarify the “unquestionably muddy” relationship between Article III and the Seventh Amendment. Yet it...The post<em>Sun Valley Orchards, LLC<br>v. United States Department of Labor</em>appeared first onHarvard Law Review.
United States v. Johnson
Drug detection dogs are critical tools in the fight against drug trafficking. However, law enforcement canines are imperfect: They sometimes incorrectly alert when performing...The post<em>United States v. Johnson</em>appeared first onHarvard Law Review.
Telogenesis: Goal Is All U Need
arXiv:2603.09476v1 Announce Type: new Abstract: Goal-conditioned systems assume goals are provided externally. We ask whether attentional priorities can emerge endogenously from an agent's internal cognitive state. We propose a priority function that generates observation targets from three epistemic gaps: ignorance...
Deep Tabular Research via Continual Experience-Driven Execution
arXiv:2603.09151v1 Announce Type: new Abstract: Large language models often struggle with complex long-horizon analytical tasks over unstructured tables, which typically feature hierarchical and bidirectional headers and non-canonical layouts. We formalize this challenge as Deep Tabular Research (DTR), requiring multi-step reasoning...
The Confidence Gate Theorem: When Should Ranked Decision Systems Abstain?
arXiv:2603.09947v1 Announce Type: new Abstract: Ranked decision systems -- recommenders, ad auctions, clinical triage queues -- must decide when to intervene in ranked outputs and when to abstain. We study when confidence-based abstention monotonically improves decision quality, and when it...